Translational Text Mining Ulf Leser Humboldt-Universität zu Berlin Berlin, Germany leser@informatik.hu-berlin.de Abstract ber of the Berlin School for Integrative Oncology (BSIO). Text Mining has become an important tool for many areas of biomedical research. Nevertheless, its impact actually is still surprisingly small, given the enormous body of knowledge published every day and the difficulties of biomedical researchers to keep an overview of relevant developments even only in their very specific fields of research. Why has the usage of some form of semantic search en- gine or large-scale information extraction pipeline not yet become the standard procedure for being up-to-date wrt related work? In this talk, I high- light some of the key issues text mining faces when it tries to become ”translational”, i.e., invade daily biomedical research. Examples are (a) the misleading focus on ”correct extraction” where it should be ”correct biological fact”, (b) the wide- spread negligence of full texts and patents, and (c) the inaccessibility of typical machine learning models for end users. Notwithstanding some tech- nical barriers, I argue that the community must invest more efforts to move closer to its users to achieve proper recognition in the field. Biography Ulf Leser studied computer science at the Tech- nische Universitt Mnchen and did his PhD at the Technische Universitt Berlin. After positions in research institutes and in the private sector, be be- came a professor for Knowledge Management in Bioinformatics at Humboldt-Universitt zu Berlin. His research focuses on scientific data manage- ment, statistical Bioinformatics, biomedical text mining and infrastructures for large-scale Bioin- formatics analysis, topics he typically approaches in interdisciplinary projects with biologists and medical doctors. He is speaker of the gradu- ate school SOAMED (Service-oriented architec- tures for medical applications) and a board mem-